Data-driven prognosis of failure detection and prediction of lithium-ion batteries-Reference-Cited by-同舟云学术

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Data-driven prognosis of failure detection and prediction of lithium-ion batteries

Published:2023-10 Issue: Volume:70 Page:108045
ISSN:2352-152X
Container-title:Journal of Energy Storage
language:en
Short-container-title:Journal of Energy Storage

Author:

Kouhestani Hamed Sadegh,Liu Lin,Wang Ruimin,Chandra Abhijit

Funder

National Aeronautics and Space Administration

NSF

National Science Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference44 articles.

1. EDTA, Electric Drive Transportation Association (EDTA), Washington Dc. 2021.

2. Electric Vehicle Outlook;BloombergNEF,2021

3. Global EV Outlook 2020: Entering the Decade of Electric Drive?. International Energy Agency (IEA), Technology Report;IEA,2020

4. A review on the key issues for lithium-ion battery management in electric vehicles;Lu;J. Power Sources,2013

5. Estimating the technical feasibility of fuel cell and battery electric vehicles for the medium and heavy duty sectors in California;Forrest;J. Appl. Energy,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Remaining Useful Life Prediction Method of PEM Fuel Cells Based on a Hybrid Model;Electronics;2023-09-14

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